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On Marginal Subgradients of Convex Functions

机译:凸函数的边际次梯度

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摘要

For a lower semicontinuous and proper convex function f with nonempty minimizer set and a point x in its domain, a marginal subgradient of f at x is a vector in df(x) with the smallest norm. We denote the norm of the marginal subgradient of f at x by g(x), it is known that the infimum of g(x) over a level set of f is nondecreasing from a lower level set to a higher level set. In this paper we study another aspect of the marginal subgradients, namely the monotonicity of the infimum of g(x) over an equidistance contour from the minimizer set. The results are applied to the study of some growth properties of the marginal subgradients.
机译:对于具有非空极小值集且其域中有点x的下半连续和适当的凸函数f,x处的f的边际次梯度是df(x)中具有最小范数的向量。我们用g(x)表示f在x处的边际次梯度的范数,已知在f的水平集合上g(x)的最小值从较低的水平集合逐渐减小到较高的水平集合。在本文中,我们研究了边际次梯度的另一方面,即从极小子集到等距轮廓上的g(x)的最小值的单调性。该结果可用于研究边缘次梯度的某些生长特性。

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